Mendis Lochana, Palaniswami Marimuthu, Brownfoot Fiona, Keenan Emerson
Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia.
Obstetric Diagnostics and Therapeutics Group, Department of Obstetrics and Gynaecology, The University of Melbourne, Heidelberg, VIC 3084, Australia.
Bioengineering (Basel). 2023 Aug 25;10(9):1007. doi: 10.3390/bioengineering10091007.
The measurement and analysis of fetal heart rate (FHR) and uterine contraction (UC) patterns, known as cardiotocography (CTG), is a key technology for detecting fetal compromise during labour. This technology is commonly used by clinicians to make decisions on the mode of delivery to minimise adverse outcomes. A range of computerised CTG analysis techniques have been proposed to overcome the limitations of manual clinician interpretation. While these automated techniques can potentially improve patient outcomes, their adoption into clinical practice remains limited. This review provides an overview of current FHR and UC monitoring technologies, public and private CTG datasets, pre-processing steps, and classification algorithms used in automated approaches for fetal compromise detection. It aims to highlight challenges inhibiting the translation of automated CTG analysis methods from research to clinical application and provide recommendations to overcome them.
胎儿心率（FHR）和子宫收缩（UC）模式的测量与分析，即产时胎心监护（CTG），是检测分娩期间胎儿窘迫的一项关键技术。临床医生通常使用这项技术来决定分娩方式，以尽量减少不良后果。为克服临床医生手动解读的局限性，人们提出了一系列计算机化的CTG分析技术。虽然这些自动化技术有可能改善患者预后，但它们在临床实践中的应用仍然有限。本综述概述了当前用于胎儿窘迫检测的自动方法中的FHR和UC监测技术、公共和私人CTG数据集、预处理步骤以及分类算法。其目的是突出阻碍自动CTG分析方法从研究转化为临床应用的挑战，并提供克服这些挑战的建议。
